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Statistical properties of agent-based models in markets with continuous double auction mechanism

Listed author(s):
  • Tseng, Jie-Jun
  • Lin, Chih-Hao
  • Lin, Chih-Ting
  • Wang, Sun-Chong
  • Li, Sai-Ping
Registered author(s):

    Real world markets display power-law features in variables such as price fluctuations in stocks. To further understand market behavior, we have conducted a series of market experiments on our web-based prediction market platform which allows us to reconstruct transaction networks among traders. From these networks, we are able to record the degree of a trader, the size of a community of traders, the transaction time interval among traders and other variables that are of interest. The distributions of all these variables show power-law behavior. On the other hand, agent-based models have been proposed to study the properties of real financial markets. We here study the statistical properties of these agent-based models and compare them with the results from our web-based market experiments. In this work, three agent-based models are studied, namely, zero-intelligence (ZI), zero-intelligence-plus (ZIP) and Gjerstad–Dickhaut (GD). Computer simulations of variables based on these three agent-based models were carried out. We found that although being the most naive agent-based model, ZI indeed best describes the properties observed in real markets. Our study suggests that the basic ingredient to produce the observed properties from real world markets could in fact be the result of a continuously evolving dynamical system with basic features similar to the ZI model.

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    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 389 (2010)
    Issue (Month): 8 ()
    Pages: 1699-1707

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    Handle: RePEc:eee:phsmap:v:389:y:2010:i:8:p:1699-1707
    DOI: 10.1016/j.physa.2009.12.034
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    1. Berardi, Luca & Serva, Maurizio, 2005. "Time and foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 403-412.
    2. Jie-Jun Tseng & Sai-Ping Li & Sun-Chong Wang, 2010. "Experimental evidence for the interplay between individual wealth and transaction network," Papers 1001.3731,
    3. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70, pages 322-322.
    4. S. C. Wang & J. J. Tseng & C. C. Tai & K. H. Lai & W. S. Wu & S. H. Chen & S. P. Li, 2008. "Network topology of an experimental futures exchange," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(1), pages 105-111, March.
    5. Gjerstad, Steven & Dickhaut, John, 1998. "Price Formation in Double Auctions," Games and Economic Behavior, Elsevier, vol. 22(1), pages 1-29, January.
    6. Luca Berardi & Maurizio Serva, 2005. "Time and foreign exchange markets," Papers physics/0504100,
    7. Smith, Vernon L, 1976. "Experimental Economics: Induced Value Theory," American Economic Review, American Economic Association, vol. 66(2), pages 274-279, May.
    8. Sun-Chong Wang & Sai-Ping Li & Chung-Ching Tai & Shu-Heng Che, 2009. "Statistical properties of an experimental political futures market," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 9-16.
    9. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    10. Scheinkman, Jose A & Woodford, Michael, 1994. "Self-Organized Criticality and Economic Fluctuations," American Economic Review, American Economic Association, vol. 84(2), pages 417-421, May.
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